| 改进的Kohonen网络及图像自适应矢量量化 |
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| 引用本文： | 王卫 蔡德钧. 改进的Kohonen网络及图像自适应矢量量化[J]. 通信学报, 1992, 13(5): 16-21 |
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| 作者姓名： | 王卫 蔡德钧 |
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| 作者单位： | 华中理工大学电信系，华中理工大学电信系，华中理工大学电信系 武汉 430074，武汉 430074，武汉 430074 |
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| 摘 要： | 本文针对图像矢量量化存在的分块效应问题,通过对Kohonen自组织模型的研究,修改了Kohonen的自组织特征映射(SOFM)算法,设计了两个DCT(离散余弦变换)域的特征值,用于图像数据块的分类。在此基础上,进一步探讨了改进的自组织特征映射(MSOFM)算法在图像自适应矢量量化中的应用。计算机模拟实验表明,MSOFM算法有效地减少了分块效应,与SOFM算法相比具有更好的性能。
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| 关 键 词： | Kohonen网络 矢量量化 神经网络 |
Modified Kohonen Self-Organization Neural Network and Adaptive Vector Quantization of Images |
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| Wang Wei,Cai Dejun and Wan Faguan. Modified Kohonen Self-Organization Neural Network and Adaptive Vector Quantization of Images[J]. Journal on Communications, 1992, 13(5): 16-21 |
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| Authors: | Wang Wei Cai Dejun Wan Faguan |
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| Abstract: | Based on the discussion of the principle of Kohonen's self-organizing feature maps(SOFM) a modified SOFM (MSOFM) algorithm is proposed to reduce blocking effect of vector quantization of images in this paper. Two eigenvalues are designed in DCT (Discret(?) Cosine Transform) domain to classify image blocks, then we discuss the application of MSOFM algorithm in adaptive vector quantization. The results of computer simulation show that the MSOFM training algorithm significantly reduces blocking effect and have a better Performance than the SOFM algorithm. |
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| Keywords: | Kohonen network Vector quantization Neural network Image compression Adaption. |
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